Key Responsibilities:
Data Pipeline Development (ETL/ELT)
- Design, develop, and maintain robust ETL/ELT pipelines for structured and semi-structured data.
- Implement data ingestion workflows using tools such as Azure Data Factory, Informatica, DBT, or Python/SQL scripts.
- Enable near real-time ingestion using Snowpipe, Streams, and Tasks.
Snowflake Development & Optimization
- Write and optimize complex SQL queries, stored procedures, views, and user-defined functions (UDFs).
- Work extensively with Snowflake features such as Time Travel, Fail-safe, Snowpipe, and SnowSQL.
- Optimize query performance using clustering keys, caching, pruning strategies, and materialized views.
- Monitor and tune warehouse performance for cost and efficiency.
Data Modeling & Warehousing
- Design and implement data models including star schema, snowflake schema, normalized, and denormalized models.
- Develop logical and physical data models for analytics and reporting systems.
- Ensure scalable and efficient data architecture for enterprise reporting needs.
Performance & Optimization
- Improve data pipeline efficiency and system performance.
- Optimize SQL workloads and data storage strategies.
- Ensure high availability and reliability of data systems.
Collaboration & Delivery
- Work with data architects, analysts, and business teams to translate requirements into scalable solutions.
- Ensure timely delivery of data engineering solutions aligned with business needs.
